5c03e07ded
Simpler story (slide decks unread -> three-bullet status email), proper Claude-chat look with avatars and bubbles on both sides. Canonical trigger prompt switched to English everywhere (homepage, architecture, both adapter generators rebuilt) - V7 consistency green, all checks pass. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PDKeXvpT6tENSvyQGLV1Uq
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esco_uri, esco_label, relation, onet_soc, source, confidence, qa_count, generator, generated
| esco_uri | esco_label | relation | onet_soc | source | confidence | qa_count | generator | generated |
|---|---|---|---|---|---|---|---|---|
| http://data.europa.eu/esco/skill/b363bb5f-2c79-40af-94da-33e06f9dee9f | apply blended learning | optional | 15-2051.00 | model-knowledge | high | 0 | gemma3:27b (prompt-designed and spot-checked by Claude) | 2026-07-10 |
apply blended learning — Data Scientist
For a Data Scientist, 'apply blended learning' isn’t about teaching courses – it’s about continuous self-improvement and knowledge sharing within teams, given the field evolves so rapidly. It means proactively combining formal training (online courses on platforms like Coursera, DataCamp, fast.ai) with practical application through personal projects, Kaggle competitions, or internal company datasets. It also involves leveraging documentation – not just reading it, but actively contributing to internal knowledge bases (e.g., Confluence pages detailing project approaches, Jupyter Notebooks shared as learning examples). Think of it as a 'learn-by-doing' approach augmented by structured online resources.
Weitere Anreicherung
Stage-2 source for future practitioner grounding: arXiv cs.LG/stat.ML (ML preprints).